Field
The invention relates to a method for assisting a driver in driving a vehicle, a driver assistance system, a computer software program product and a vehicle including such driver assistance system.
Description of the Related Art
Over the last 50 years, the use of self-propelled vehicles for individual transportation and driving developed rapidly. In major parts of the world, nearly every household owns at least one such vehicle, for example a car. Accordingly, the density of traffic on the roads increased also rapidly. Participating in such dense traffic therefore, for most people, became no longer enjoyable but a burden. Thus, an increasing need for improved comfort in driving can be recognized. In order to comply with these needs, car manufacturers seek to assist a driver so that the driver can focus on the remaining actions that need to be taken when driving a car. For example, early driver assistance systems introduced a cruise control which assisted the driver in maintaining a constant speed even on an inclined road by automatically adapting the throttle of the engine. Early driver assistance systems of course were very limited in their capability. The example of the cruise control makes this obvious, because at the beginning no autonomous braking was included. Consequently, driving down a hill would lead to an undesired acceleration. Later systems overcame such deficiencies since they include also a brake system in the cruise control system. Thus, they were able to maintain a target speed independent of any inclination of the road. But still no reaction to the needs of the traffic environment was included.
A newer generation of driver assistance systems is called advanced driver assistance systems. Such systems take into consideration information about the environment so that for example warning signals in case of dangerous situations can be output or even an automatic control of the car may be performed in order to mitigate or entirely prevent critical situations. As an example, an adaptive cruise control senses the distance between the car equipped with such a system (host vehicle) and the preceding car and adapts the speed automatically. A first step towards an improved driver assistance system was made. Another example is an emergency braking system that can automatically initiate an emergency braking in case that an object can be recognized directly in front of the vehicle. These two examples given above are rather simple to implement, because the only information that is needed is information of the size of a free space in the longitudinal direction of the car. But since only a very limited part of the environment of the vehicle is taken into consideration for evaluation of the traffic situation, the capability and the usefulness of such system is also limited. Instead of braking for example it could be more advantageous to consider a lateral avoidance maneuver (lane change) so that no emergency braking would be needed. This of course would immediately need to take into account a lot more information about the environment of the host vehicle. In particular, determining strategies for vehicle maneuver in dense traffic needs anticipation of the future traffic situation or development of a scene so that for example a minimization of the risk of an accident may be achieved. Development of driver assistance systems does have the target to realize autonomous driving one day. It is obvious that this development therefore needs simultaneous consideration of information with an increasing complexity and in particular to take into consideration a plurality of behavior options of the traffic participants of a scene. Although, the performance of computing processors increases rapidly it is still a problem to make real time evaluation of situations due to the huge amount of data including the information about the environment of a vehicle.
The influence of the environment on the behavior of a vehicle driver is needed to be taken into consideration for anticipation of future traffic situations. The car the driver of which shall be assisted in driving (EGO-vehicle, host vehicle) is of course also part of the scene and thus covers a particular part of surface of this traffic scene. Which part it is, depends of course on the behavior of the host vehicle. The entire area of a traffic situation is a combination of area units each of these units having a particular quality. In this context, quality means that an estimation is given how likely it is that this particular unit may be traversed by a vehicle. For example, those area units occupied by another car have a very low probability to be traversed by another traffic object. An area unit corresponding to a free road on the other hand has a very high probability to be traversed by a car. As this easy example already reveals for anticipation of future traffic situations, it is most important that every part and object in the environment of the host vehicle is known and particular regarding its spatial extent and position. For the coverage of the environment of the host vehicle, there have already been a few proposals like for example in WO 2013/087067 A1 or EP 1 731 922 A1. But occupancy of a particular area in the environment of a host vehicle is only one aspect. Other rules and structures that cannot be taken into consideration by such occupancy grids nevertheless have a strong influence on the behavior of any traffic participant in a traffic situation. For example, although a zebra crossing is currently not used by a pedestrian who is already recognized besides the zebra crossing on the pavement, at the moment is a free road ahead. But there is a reasonable chance that the pedestrian stepping onto the zebra crossing and will cause a traffic participant to brake in order to stop in front of the zebra crossing. This example illustrates that the environment may change with time. As long as no person is on the zebra crossing, it might be considered a free lane ahead. But as soon as a person steps towards the zebra crossing, the zebra crossing has to be considered a forbidden area since the driver is demanded to let the pedestrian cross. Information about the presence and the position of a zebra crossing or information where the own lane, the opposing lane or a highway exit or the like is, is called semantics. In order to describe the development of a traffic situation that allows evaluation and maybe allows a suggestion for a particular behavior, it is thus necessary to have an environment representation that covers spatial, temporal and semantic information. Since this is a huge amount of information data there is a need for an efficient environment representation that includes all the information needed for a reasonable evaluation but is not burdened with information that is unnecessary.
EP 2 339 375 A2 is a first attempt to limit the complexity in which an environment representation is made. Instead of describing all the objects with their spatial relation, it is suggested to rather make a prediction of the change of the free space. Thus, the free space can be identified as being one object that transforms with time. Although this in fact reduces the amount of data that is needed to describe a free space it has a big disadvantage. The limitation to information about the free space on the other hand results in the disability of predicting future movement behavior of other traffic participants since they are no longer part of the information about the environment.